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Change warning message to user exception for model type and task type mismatch #1330

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merged 3 commits into from
Apr 11, 2022
Merged

Change warning message to user exception for model type and task type mismatch #1330

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7f26225
Change warning message to user exception for model type and task type…
gaugup Apr 8, 2022
d3d2772
Merge branch 'main' into gaugup/CovertWarningToException
gaugup Apr 11, 2022
a17a47a
Fix flake8 errors
gaugup Apr 11, 2022
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4 changes: 2 additions & 2 deletions responsibleai/responsibleai/rai_insights/rai_insights.py
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Original file line number Diff line number Diff line change
Expand Up @@ -323,8 +323,8 @@ def _validate_model_analysis_input_parameters(

if task_type == ModelTask.REGRESSION:
if hasattr(model, SKLearn.PREDICT_PROBA):
warnings.warn(
'INVALID-TASK-TYPE-WARNING: The regression model'
raise UserConfigValidationException(
'The regression model'
'provided has a predict_proba function. '
'Please check the task_type.')
else:
Expand Down
23 changes: 13 additions & 10 deletions responsibleai/tests/test_model_analysis_validations.py
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Original file line number Diff line number Diff line change
Expand Up @@ -13,8 +13,9 @@
from responsibleai.modelanalysis.model_analysis import ModelAnalysis

from .common_utils import (create_binary_classification_dataset,
create_cancer_data, create_iris_data,
create_lightgbm_classifier)
create_cancer_data, create_housing_data,
create_iris_data, create_lightgbm_classifier,
create_sklearn_random_forest_regressor)


class TestModelAnalysisValidations:
Expand Down Expand Up @@ -234,10 +235,10 @@ def test_model_analysis_incorrect_task_type(self):
X_train['target'] = y_train
X_test['target'] = y_test

err_msg = ('INVALID-TASK-TYPE-WARNING: The regression model'
err_msg = ('The regression model'
'provided has a predict_proba function. '
'Please check the task_type.')
with pytest.warns(UserWarning, match=err_msg):
with pytest.raises(UserConfigValidationException, match=err_msg):
ModelAnalysis(
model=model,
train=X_train,
Expand Down Expand Up @@ -424,18 +425,20 @@ def test_desired_class_not_set(self):
method='random')

def test_desired_range_not_set(self):
X_train, y_train, X_test, y_test, _ = \
create_binary_classification_dataset()
X_train, X_test, y_train, y_test, feature_names = \
create_housing_data()

model = create_lightgbm_classifier(X_train, y_train)
X_train['target'] = y_train
X_test['target'] = y_test
model = create_sklearn_random_forest_regressor(X_train, y_train)
X_train = pd.DataFrame(X_train, columns=feature_names)
X_test = pd.DataFrame(X_test, columns=feature_names)
X_train['TARGET'] = y_train
X_test['TARGET'] = y_test

model_analysis = ModelAnalysis(
model=model,
train=X_train,
test=X_test,
target_column='target',
target_column='TARGET',
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task_type='regression')
with pytest.raises(
UserConfigValidationException,
Expand Down
17 changes: 10 additions & 7 deletions responsibleai/tests/test_rai_insights_validations.py
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Original file line number Diff line number Diff line change
Expand Up @@ -13,8 +13,9 @@
from responsibleai.exceptions import UserConfigValidationException

from .common_utils import (create_binary_classification_dataset,
create_cancer_data, create_iris_data,
create_lightgbm_classifier)
create_cancer_data, create_housing_data,
create_iris_data, create_lightgbm_classifier,
create_sklearn_random_forest_regressor)

TARGET = 'target'

Expand Down Expand Up @@ -236,10 +237,10 @@ def test_model_analysis_incorrect_task_type(self):
X_train[TARGET] = y_train
X_test[TARGET] = y_test

err_msg = ('INVALID-TASK-TYPE-WARNING: The regression model'
err_msg = ('The regression model'
'provided has a predict_proba function. '
'Please check the task_type.')
with pytest.warns(UserWarning, match=err_msg):
with pytest.raises(UserConfigValidationException, match=err_msg):
RAIInsights(
model=model,
train=X_train,
Expand Down Expand Up @@ -502,10 +503,12 @@ def test_desired_class_not_set(self):
method='random')

def test_desired_range_not_set(self):
X_train, y_train, X_test, y_test, _ = \
create_binary_classification_dataset()
X_train, X_test, y_train, y_test, feature_names = \
create_housing_data()

model = create_lightgbm_classifier(X_train, y_train)
model = create_sklearn_random_forest_regressor(X_train, y_train)
X_train = pd.DataFrame(X_train, columns=feature_names)
X_test = pd.DataFrame(X_test, columns=feature_names)
X_train[TARGET] = y_train
X_test[TARGET] = y_test

Expand Down